Heteroskedasticity-Consistent Estimation of the Variance-Covariance Matrix for the Almost Ideal Demand System [PDF]
In this note I demonstrate the previously overlooked fact that if the AIDS aggregate demand model is constructed as the aggregation of individual consumer demands, then the error structure for any individual equation is necessarily heteroskedastic unless
Melvyn A. Fuss
core
Multivariate spectral reconstruction of stap covariance matrices: Toeplitz-block solution
, 2008 In space-time adaptive processing (STAP) applications, temporally stationary clutter results in a Toeplitz-block clutter covariance matrix. In the reduced-order parametric matched filter STAP technique, this covariance matrix is reconstructed from a ...
Nicholas K. Spencer +5 more
core +1 more source
Portfolio risk measurement: the estimation of the covariance of stock returns [PDF]
A covariance matrix of asset returns plays an important role in modern portfolio analysis and risk management. Despite the recent interests in improving the estimation of a return covariance matrix, there remain many areas for further investigation. This
Liu, Lan
core
Econometric Computing with HC and HAC Covariance Matrix Estimators [PDF]
Data described by econometric models typically contains autocorrelation and/or heteroskedasticity of unknown form and for inference in such models it is essential to use covariance matrix estimators that can consistently estimate the covariance of the ...
Achim Zeileis
core
Some Heteroskedasticity Consistent Covariance Matrix Estimators with Improved Finite Sample Properties [PDF]
We examine several modified versions of the heteroskedasticity-consistent covariance matrix estimator of Hinkley and White. On the basis of sampling experiments which compare the performance of quasi t statistics, we find that one estimator, based on the
Halbert White, James G. MacKinnon
core
Consistency of Kernel Estimators of Heteroscedastic and Autocorrelated Covariance Matrices [PDF]
Conditions are derived for the consistency of kernel estimators of the covariance matrix of a sum of vectors of dependent heterogeneous random variables, which match those of the currently best-known conditions for the central limit theorem, as required ...
Jong, R.M. de, Davidson, J.
core
On the estimation of covariance matrices using panel data artificial regressions
, 2003 The use of artificial regressions to compute the variance of the difference of pairs of panel data estimators that cannot be ranked in terms of efficiency is considered.
Patacchini, Eleonora
core +1 more source
ROBUST COVARIANCE MATRIX ESTIMATION: "HAC" Estimates with Long Memory/Antipersistence Correction [PDF]
Smoothed nonparametric estimates of the spectral density matrix at zero frequency have been widely used in econometric inference, because they can consistently estimate the covariance matrix of a partial sum of a possibly dependent vector process.
Peter M Robinson
core
Robust Adaptive Beamforming with Sensor Position Errors Using Weighted Subspace Fitting-Based Covariance Matrix Reconstruction. [PDF]
Sensors (Basel), 2018 Chen P, Yang Y, Wang Y, Ma Y.
europepmc +1 more source
On the estimation of covariance matrices using panel data artificial regressions [PDF]
The use of artificial regressions to compute the variance of the difference of pairs of panel data estimators that cannot be ranked in terms of efficiency is considered.
Patacchini, Eleonora
core